Catalog of EQ-5D-3L Health-Related Quality-of-Life Scores for 199 Chronic Conditions and Health Risks in Denmark

Background. Assessments of health-related quality of life (HRQoL) are essential in estimating quality-adjusted life-years. It is sometimes not feasible to collect primary HRQoL data, and reliable secondary sources are necessary. Current "off-the-shelf" HRQoL catalogs are based on older diagnosis classifications and include a limited number of diseases. This article aims to provide 1) a Danish EQ-5D-3L-based HRQoL catalog for 199 nationally representative chronic conditions based on ICD-10 codes and 2) a complementary model-based catalog controlling for age, sex, comorbidities, lifestyle, and health risks. Design. A total of 55,616 respondents from 3 national health survey samples were pooled and combined with 7 national registers containing patient-level information on diagnoses, health care activity, and sociodemographics. EQ-5D-3L data were converted to utility scores using the Danish EQ-5D-3L value set to estimate the mean utility for each chronic disease population. Adjusted limited dependent variable mixture models were estimated and used to provide a regression-based catalog of utilities/disutilities. Results. Diseases with the lowest mean EQ-5D score in the Danish population were systemic sclerosis (M34; score = 0.432), fibromyalgia (M797; score = 0.490), rheumatism (M790; score = 0.515), dementia (F00, G30; score = 0.546), posttraumatic stress syndrome (F431; score = 0.557), and systemic atrophies (G10-G14; score = 0.583. Based on the estimated models, the largest estimated disutilities were cystic fibrosis, cerebral palsy, depression, dorsalgia, sclerosis, and fibromyalgia. Lifestyle factors, including perceived stress, loneliness, and body mass index, were also significantly associated with low HRQoL. Conclusions. This study provides a comprehensive nationally representative catalog and a model-based catalog of EQ-5D-3L-based HRQoL scores for Denmark that can be used to describe aspects of disease burden and allocate resources within health care. Additional Stata programs are also provided to facilitate predictions in other populations.

Highlights

A Danish national representative catalog of health-related quality-of-life scores for 199 chronic conditions is presented, which provides population estimates for chronic conditions subgroups that can be used for health economic evaluation.Two separate regression models of EQ-5D-3L utility scores with different sets of control variables are estimated to allow researchers to adjust for differences in the composition of the subgroups and provide a tool that can be used in other settings.Results indicate that health-related quality of life varies across disease groups but is lowest for renal disease, mental and behavioral disorders, benign neoplasms and diseases of the blood, digestive systems, and nervous systems.Health risks and lifestyle factors such as perceived stress, loneliness, and a large body mass index are highly correlated with health-related quality of life, and, in many cases, the correlation is higher than with individual diseases.

Catalog of EQ-5D-3L Health-Related Quality-of-Life Scores for 199 Chronic Conditions and Health Risks in Denmark

Background. Assessments of health-related quality of life (HRQoL) are essential in estimating quality-adjusted life-years. It is sometimes not feasible to collect primary HRQoL data, and reliable secondary sources are necessary. Current "off-the-shelf" HRQoL catalogs are based on older diagnosis classifications and include a limited number of diseases. This article aims to provide 1) a Danish EQ-5D-3L-based HRQoL catalog for 199 nationally representative chronic conditions based on ICD-10 codes and 2) a complementary model-based catalog controlling for age, sex, comorbidities, lifestyle, and health risks. Design. A total of 55,616 respondents from 3 national health survey samples were pooled and combined with 7 national registers containing patient-level information on diagnoses, health care activity, and sociodemographics. EQ-5D-3L data were converted to utility scores using the Danish EQ-5D-3L value set to estimate the mean utility for each chronic disease population. Adjusted limited dependent variable mixture models were estimated and used to provide a regression-based catalog of utilities/disutilities. Results. Diseases with the lowest mean EQ-5D score in the Danish population were systemic sclerosis (M34; score = 0.432), fibromyalgia (M797; score = 0.490), rheumatism (M790; score = 0.515), dementia (F00, G30; score = 0.546), posttraumatic stress syndrome (F431; score = 0.557), and systemic atrophies (G10-G14; score = 0.583. Based on the estimated models, the largest estimated disutilities were cystic fibrosis, cerebral palsy, depression, dorsalgia, sclerosis, and fibromyalgia. Lifestyle factors, including perceived stress, loneliness, and body mass index, were also significantly associated with low HRQoL. Conclusions. This study provides a comprehensive nationally representative catalog and a model-based catalog of EQ-5D-3L-based HRQoL scores for Denmark that can be used to describe aspects of disease burden and allocate resources within health care. Additional Stata programs are also provided to facilitate predictions in other populations.

HIGHLIGHTS

A Danish national representative catalog of health-related quality-of-life scores for 199 chronic conditions is presented, which provides population estimates for chronic conditions subgroups that can be used for health economic evaluation.Two separate regression models of EQ-5D-3L utility scores with different sets of control variables are estimated to allow researchers to adjust for differences in the composition of the subgroups and provide a tool that can be used in other settings.Results indicate that health-related quality of life varies across disease groups but is lowest for renal disease, mental and behavioral disorders, benign neoplasms and diseases of the blood, digestive systems, and nervous systems.Health risks and lifestyle factors such as perceived stress, loneliness, and a large body mass index are highly correlated with health-related quality of life, and, in many cases, the correlation is higher than with individual diseases.

Mapping analysis to predict EQ-5D-5 L utility values based on the Oxford Hip Score (OHS) and Oxford Knee Score (OKS) questionnaires in the Spanish population suffering from lower limb osteoarthritis

BACKGROUND

The EQ-5D-5 L is a quality-of-life questionnaire based on individuals' preferences that is widely employed for cost-effectiveness analysis. Given the current demand for mapping algorithms to directly assign "utilities", this study aimed to generate different mapping models for predicting EQ-5D-5 L utility values based on scores of the Oxford Hip Score (OHS) and Oxford Knee Score (OKS) questionnaires provided by patients suffering from hip and knee osteoarthritis (OA), respectively, and to assess the predictive capability of these functions.

METHODS

This was a prospective, observational study. Following the criteria of the American Rheumatism Association, 361 patients with hip OA and 397 with knee OA from three regions in Spain were included. Health-related quality of life (HRQoL) was assessed through the EQ-5D-5 L general questionnaire and the OHS and OKS specifically for lower limb OA. Based on the scores on the OHS and OKS questionnaires, EQ-5D-5 L utilities were estimated using 4 models: ordinary least squares (OLS), Tobit, generalized linear model (GLM), and beta regression (Breg). The models were validated on the same patients after 6 months: the mean absolute error (MAE) and mean squared error (MSE) with their 95% confidence intervals (CI), mean values of standard errors (SE), intraclass correlation coefficients (ICC), and Bland-Altman plots were obtained.

RESULTS

The lowest MAEs were obtained using GLM and Breg models, with values of 0.1103 (0.0993-0.1214) and 0.1229 (0.1102-0.1335) for hip OA, and values of 0.1127 (0.1014-0.1239) and 0.1141 (0.1031-0.1251) for knee OA. MSE values were also lower using GLM and Breg. ICCs between predicted and observed values were around or over the 0.8 cut-off point. Bland-Altman plots showed an acceptable correlation, but precision was lower for subjects with worse HRQoL, which was also evident when comparing MAEs of the bottom and top halves of the utilities scale. Predictive equations for utilities based on OHS/OKS scores were proposed.

CONCLUSIONS

The OHS and OKS scores allow for estimating EQ-5D-5 L utility indexes for patients with hip and knee OA, respectively, with adequate validity and precision. GLM and Breg produce the best predictions. The predictive power of proposed equations is more consistent for subjects in better health condition.

Mapping WOMAC Onto the EQ-5D-5L Utility Index in Patients With Hip or Knee Osteoarthritis

OBJECTIVES

To map the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) onto the EQ-5D-5L in patients with hip or knee osteoarthritis (OA).

METHODS

A prospective observational study was conducted on 758 patients with hip or knee OA who completed the EQ-5D-5L and WOMAC questionnaires, of whom 644 completed them both again 6 months later. Baseline data were used to derive mapping functions. Generalized additive models were used to identify to which powers the WOMAC subscales should be raised to achieve a linear relationship with the response. For the modeling, general linear models (GLM), Tobit models, and beta regression models were used. Age, sex, and affected joints were also considered. Preferred models were selected based on Akaike and Bayesian information criteria, adjusted R², mean absolute error (MAE), and root mean squared error (RMSE). The functions were validated with the follow-up data using MAE, RMSE, and the intraclass correlation coefficient.

RESULTS

The preferred models were a GLM with Pain²+Pain³+Function+Pain·Function as covariates and a beta model with Pain³+Function+Function²+Function³ as covariates. The adjusted R² were similar (0.6190 and 0.6136, respectively). The predictive performance of these models in the validation sample was similar and both models showed an overprediction for health states worse than death.

CONCLUSION

To our knowledge, these are the first functions mapping the WOMAC onto the EQ-5D-5L in patients with hip or knee OA. They showed an acceptable fit and precision and could be very useful for clinicians and researchers when cost-effectiveness studies are needed and generic preference-based health-related quality of life instruments to derive utilities are not available.

Parallel Valuation: A Direct Comparison of EQ-5D-3L and EQ-5D-5L Societal Value Sets

OBJECTIVE

To compare and contrast EQ-5D-5L (5L) and EQ-5D-3L (3L) health state values derived from a common sample.

METHODS

Data from the 2017 US EQ-5D valuation study were analyzed. Value sets were estimated with random-effects linear regression based on composite time trade-off (cTTO) valuations for 3L and 5L health states with 2 approaches to model specification: main effects only and additional N3/N45 terms. Properties of the descriptive system and value set characteristics were compared by examining distributions of predicted index scores, ceiling effects, and single-level transition values from adjacent corner health states. Mean transition values were calculated for all predicted 3L and 5L health states and plotted against baseline index scores.

RESULTS

A total of 1062 respondents were included in the analysis. The observed mean cTTO values for the worst possible 3L and 5L health states were -0.423 and -0.343, respectively. The range of scale was larger with the 3L, compared to the 5L, for both main effects and N term models. Values for the mildest 5L health states (range, 0.857-0.924) were similar to 11111 for the 3L. Parameter estimates for matched dimension levels differed by <|0.07| except for the most severe level of Mobility. For the main effects model, 3L mean transition values were greater for more severe baseline 3L index scores, whereas 5L mean transition values remained constant irrespective of the baseline index score.

CONCLUSIONS

Compared to the 3L, the 5L exhibited a lower ceiling effect and improved measurement properties. There was a larger range of scale for the 3L compared to 5L; however, this difference was driven by differences in preference for the most severe level of problems in Mobility.

Impact of allergies on health-related quality of life in patients with asthma

Objective: To estimate the health-related quality of life (HRQoL) and health utilities among asthma patients with and without comorbid allergies in a managed care population.Methods: This was a retrospective analysis of patient survey responses and pharmacy claims from the Observational Study of Asthma Control and Outcomes (OSACO). Patients ≥12 years-old with persistent asthma received four identical surveys between April-2011 and December-2012. The presence of allergy was identified by a positive response to a survey question about hay fever/seasonal allergies and ≥1 diagnosis-related ICD-9-CM code(s) for allergic conditions. HRQoL instruments included generic utility (EQ-5D-3L [including VAS]), asthma-specific utility (AQL-5D) and asthma-specific health status (Mini Asthma Quality of Life Questionnaire [MiniAQLQ]). Median regression was used for utility scores and Least Squares regression for MiniAQLQ, adjusting for sociodemographic characteristics and smoking.Results: Of the 2681 asthmatics who completed the first survey in the OSACO study, 971 had comorbid allergies. After adjusting for covariates, asthma patients with comorbid allergies had significantly lower MiniAQLQ scores than patients without allergies (-0.489 [95% CI -0.570, -0.409]; p < 0.01), with the greatest decrement/impairment observed for the environmental stimuli domain (-0.729 [95% CI -0.844, -0.613]; p < 0.01). Utility scores were also statistically significantly lower for asthma patients with comorbid allergies compared to those without allergies (EQ-5D, -0.031 [95% CI -0.047, -0.015]; AQL-5D, -0.036 [95% CI -0.042, -0.029]; p < 0.01 each).Conclusions: The presence of allergies with persistent asthma is associated with a significant deleterious impact on several different measures of HRQoL.

Process utilities for topical treatment in atopic dermatitis

Purpose

Management of atopic dermatitis (AD) typically requires application of topical treatments, often multiple times a day. The cosmetic properties and burdensome application of these treatments can be detrimental to quality of life (QoL). Patients who achieve good disease control through use of systemic therapies may reduce the frequency and amount of topical applications, improving QoL. This study aimed to quantify the utility and disutility for topical AD treatment processes.

Methods

Seven vignettes describing different skincare regimens for people with moderate-to-severe AD were developed with input from healthcare professionals. 484 respondents from the general population completed time trade-off items for each vignette. Utility values for each regimen, and disutilities associated with the impact of changes to skincare regimens, were calculated. Analysis of variance assessed differences between skincare regimens.

Results

As skincare regimens increased in intensity (0.7968 for the most intense; 0.9999 for the least), utility values decreased. There were no statistically significant differences between skincare regimens followed by patients with good disease control (0.9862 to 0.9999); however, when compared to those involving topical corticosteroids and emollient combinations (0.7968 to 0.8835), significant differences were observed (p < 0.001). The largest disutilities (0.1521 to 0.1705) were between skincare regimens describing the use of topical corticosteroids plus emollient and those followed by patients with good disease control.

Conclusions

The application of topical treatments has a detrimental effect on QoL, which increases with the duration and frequency of applications. Further research is needed to investigate how health and process utilities interact and both can be integrated into medical decision-making.

Electronic supplementary material

The online version of this article (10.1007/s11136-019-02174-0) contains supplementary material, which is available to authorized users.

Should Cost-Effectiveness Analysis Include the Cost of Consumption Activities? AN Empirical Investigation

There has been a debate on whether cost-effectiveness analysis should consider the cost of consumption and leisure time activities when using the quality-adjusted life year as a measure of health outcome under a societal perspective. The purpose of this study was to investigate whether the effects of ill health on consumptive activities are spontaneously considered in a health state valuation exercise and how much this matters. The survey enrolled patients with inflammatory bowel disease in Germany (n = 104). Patients were randomized to explicit and no explicit instruction for the consideration of consumption and leisure effects in a time trade-off (TTO) exercise. Explicit instruction to consider non-health-related utility in TTO exercises did not influence TTO scores. However, spontaneous consideration of non-health-related utility in patients without explicit instruction (60% of respondents) led to significantly lower TTO scores. Results suggest an inclusion of consumption costs in the numerator of the cost-effectiveness ratio, at least for those respondents who spontaneously consider non-health-related utility from treatment. Results also suggest that exercises eliciting health valuations from the general public may include a description of the impact of disease on consumptive activities.

Mapping Functions in Health-Related Quality of Life: Mapping from Two Cancer-Specific Health-Related Quality-of-Life Instruments to EQ-5D-3L

Background. Clinical trials in cancer frequently include cancer-specific measures of health but not preference-based measures such as the EQ-5D that are suitable for economic evaluation. Mapping functions have been developed to predict EQ-5D values from these measures, but there is considerable uncertainty about the most appropriate model to use, and many existing models are poor at predicting EQ-5D values. This study aims to investigate a range of potential models to develop mapping functions from 2 widely used cancer-specific measures (FACT-G and EORTC-QLQ-C30) and to identify the best model. Methods. Mapping models are fitted to predict EQ-5D-3L values using ordinary least squares (OLS), tobit, 2-part models, splining, and to EQ-5D item-level responses using response mapping from the FACT-G and QLQ-C30. A variety of model specifications are estimated. Model performance and predictive ability are compared. Analysis is based on 530 patients with various cancers for the FACT-G and 771 patients with multiple myeloma, breast cancer, and lung cancer for the QLQ-C30. Results. For FACT-G, OLS models most accurately predict mean EQ-5D values with the best predicting model using FACT-G items with similar results using tobit. Response mapping has low predictive ability. In contrast, for the QLQ-C30, response mapping has the most accurate predictions using QLQ-C30 dimensions. The QLQ-C30 has better predicted EQ-5D values across the range of possible values; however, few respondents in the FACT-G data set have low EQ-5D values, which reduces the accuracy at the severe end. Conclusions. OLS and tobit mapping functions perform well for both instruments. Response mapping gives the best model predictions for QLQ-C30. The generalizability of the FACT-G mapping function is limited to populations in moderate to good health.

Population norms for the EQ-5D index scores using Singapore preference weights

PURPOSE

To provide norms for the EQ-5D index scores based on Singapore preference weights according to age, sex, ethnicity, and language version and compare the EQ-5D index scores for respondents with and without psychiatric disorders and chronic medical conditions.

METHODS

The Singapore Mental Health Study was a cross-sectional epidemiological survey of a nationally representative sample of the resident (citizens and permanent residents) population in Singapore. The diagnoses of psychiatric disorders were established using the World Mental Health Composite International Diagnostic Interview version 3.0 (CIDI 3.0). Index scores were derived using the Singapore preference weights.

RESULTS

In general, the mean EQ-5D index score using Singapore preference weights decreased with increased age. The EQ-5D Malay version reported lower mean EQ-5D index than the English version. In multivariate analysis, the mean EQ-5D index for respondents with MDD, dysthymia, bipolar disorder, GAD, OCD, diabetes, hypertension, arthritis or rheumatism, neurological condition, stroke or major paralysis, heart attack, back problems, stomach ulcer, kidney failure, migraine headaches, and chronic lung disease was significantly lower than those without these conditions.

CONCLUSIONS

These findings support the use of the Singapore preference weights for EQ-5D valuations when measuring health-related quality of life and comparing the health burden of psychiatric and chronic physical conditions among adults in Singapore.

Estimation of utility values from visual analog scale measures of health in patients undergoing cardiac surgery

Introduction

In health economic evaluations, mapping can be used to estimate utility values from other health outcomes in order to calculate quality adjusted life-years. Currently, no methods exist to map visual analog scale (VAS) scores to utility values. This study aimed to develop and propose a statistical algorithm for mapping five dimensions of health, measured on VASs, to utility scores in patients suffering from cardiovascular disease.

Methods

Patients undergoing coronary artery bypass grafting at Aalborg University Hospital in Denmark were asked to score their health using the five VAS items (mobility, self-care, ability to perform usual activities, pain, and presence of anxiety or depression) and the EuroQol 5 Dimensions questionnaire. Regression analysis was used to estimate four mapping models from patients’ age, sex, and the self-reported VAS scores. Prediction errors were compared between mapping models and on subsets of the observed utility scores. Agreement between predicted and observed values was assessed using Bland–Altman plots.

Results

Random effects generalized least squares (GLS) regression yielded the best results when quadratic terms of VAS scores were included. Mapping models fitted using the Tobit model and censored least absolute deviation regression did not appear superior to GLS regression. The mapping models were able to explain approximately 63%–65% of the variation in the observed utility scores. The mean absolute error of predictions increased as the observed utility values decreased.

Conclusion

We concluded that it was possible to predict utility scores from VAS scores of the five dimensions of health used in the EuroQol questionnaires. However, the use of the mapping model may be inappropriate in more severe conditions.

Evidence of spillover of illness among household members: EQ-5D scores from a US sample

BACKGROUND/OBJECTIVES

The effects of illness extend beyond the individual to caregivers and family members. This study identified evidence of spillover of illness onto household members' health-related quality of life.

METHODS

Medical Expenditures Panel Survey (MEPS) data from 2000-2003 were analyzed using multivariable regression to identify spillover of household members' chronic conditions onto individuals' health-related quality of life as measured by the EuroQol-5D (EQ-5D) score (N = 24,188). Spillover was assessed by disease category, timing of occurrence (preexisting or new conditions), and age of the household member (adult or child).

RESULTS

Controlling for an individual's own health conditions and other known predictors of EQ-5D scores, the authors found that the odds of an individual reporting full health (an EQ-5D score of 1.0, relative to <1.0) were lower with the presence of existing mental (odds ratio 0.71; 95% confidence interval, 0.64-0.79), respiratory (0.85; 0.75-0.97), and musculoskeletal (0.83; 0.75-0.93) conditions among adults and with mental (0.72; 0.62-0.82) and respiratory (0.80; 0.81-0.96) conditions among children in the household. The odds of an individual reporting full health were also lower for newly occurring chronic conditions in the household, including adults' mental (0.79; 0.65-0.97), nervous/sensory system (0.76; 0.61-0.96), and musculoskeletal (0.78; 0.65-0.95) conditions and children's mental conditions (0.64; 0.48-0.86). EQ-5D dimensions may be unsuited to fully capture spillover utility among household members, and MEPS lacks condition severity and caregiver status among household members.

CONCLUSIONS

Evidence from a US sample suggests that individuals who live with chronically ill household members have lower EQ-5D scores than those who live either alone or with healthy household members. Averting spillover effects may confer substantial additional benefit at the population level for interventions that prevent or alleviate conditions that incur such effects.